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Countries have pledged to different national and international environmental agreements, most prominently the climate change mitigation targets of the Paris Agreement. Accounting for carbon stocks and flows (fluxes) is essential for countries that have recently adopted the United Nations System of Environmental-Economic Accounting - ecosystem accounting framework (UNSEEA) as a global statistical standard. In this paper, we analyze how spatial carbon fluxes can be used in support of the UNSEEA carbon accounts in five case countries with available in-situ data. Using global multi-date biomass map products and other remotely sensed data, we mapped the 2010–2018 carbon fluxes in Brazil, the Netherlands, the Philippines, Sweden and the USA using National Forest Inventory (NFI) and local biomass maps from airborne LiDAR as reference data. We identified areas that are unsupported by the reference data within environmental feature space (6–47% of vegetated country area); cross-validated an ensemble machine learning (RMSE=9–39 Mg C ha - 1 and R 2 =0.16–0.71) used to map carbon fluxes with prediction intervals; and assessed spatially correlated residuals (<5 km) before aggregating carbon fluxes from 1-ha pixels to UNSEEA forest classes. The resulting carbon accounting tables revealed the net carbon sequestration in natural broadleaved forests. Both in plantations and in other woody vegetation ecosystems, emissions exceeded sequestration. Overall, our estimates align with FAO-Forest Resource Assessment and national studies with the largest deviations in Brazil and USA. These two countries used highly clustered reference data, where clustering caused uncertainty given the need to extrapolate to under-sampled areas. We finally provide recommendations to mitigate the effect of under-sampling and to better account for the uncertainties once carbon stocks and flows need to be aggregated in relatively smaller countries. These actions are timely given the global initiatives that aim to upscale UNSEEA carbon accounting. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to understand how the FUCAPE 120% Sustainable project promotes sustainable development in higher education. The project was conceived and implemented by FUCAPE Business School, a private higher education institution (HEI) specialised in business, located in Vitória, Espírito Santo, Brazil. Design/methodology/approach: The approach of the study was qualitative research based on a case study. Data were collected through semi-structured interviews with 12 stakeholders involved in FUCAPE 120% Sustainable. Findings: The results indicate that FUCAPE 120% Sustainable is a project formed from 18 sustainable actions incorporated on the campus of FUCAPE Business School. Most of the project's actions are connected to the triple bottom line (TBL) and linked to sustainable development goals (SDGs), particularly SDG12 (responsible consumption and production), SDG13 (climate action) and SDG17 (partnerships for the goals). Research limitations/implications: This study contributes to the literature by extending information on sustainability in HEIs, focusing specifically on a business HEI. Practical implications: This is an innovative project that can serve as a model for other HEIs, with due adaptations. As business HEIs do not usually have laboratories, they may be considered to have little effect on the environment. However, this study found that business HEIs can have a relevant impact on the environment, and the adoption of sustainable actions can minimise adverse effects. Originality/value: Various sustainability projects and actions are developed and implemented by HEIs, but studies analysing the projects in business HEIs or studies linking the actions of the project to the TBL theory and SDGs are scarce. Sustainable business HEI-based projects may provide future managers a more inter-disciplinary and sustainable vision focused on the TBL and SDGs. [ABSTRACT FROM AUTHOR]

Forests serve a crucial role in our fight against climate change. Secondary forests provide important potential for conservation of biodiversity and climate change mitigation. In this paper, we explore whether collective property rights in the form of indigenous territories (ITs) lead to higher rates of secondary forest growth in previously deforested areas. We exploit the timing of granting of property rights, the geographic boundaries of ITs and two different methods, regression discontinuity design and differencein-difference, to recover causal estimates. We find strong evidence that indigenous territories with secure tenure not only reduce deforestation inside their lands but also lead to higher secondary forest growth on previously deforested areas. After receiving full property rights, land inside ITs displayed higher secondary forest growth than land outside ITs, with an estimated effect of 5% using our main RDD specification, and 2.21% using our difference-in-difference research design. Furthermore, we estimate that the average age of secondary forests was 2.2 y older inside ITs with secure tenure using our main RDD specification, and 2.8 y older when using our difference-indifference research design. Together, these findings provide evidence for the role that collective property rights can play in the push to restore forest ecosystems. [ABSTRACT FROM AUTHOR]

Adapting reservoir operation to a changing climate is important to improve water system performance toward benefits including water security, and energy production. However, managers still need to know if and how reoperation can also assist long-term mitigation of climate change impacts on aquatic ecosystems, creating, for example, opportunities to revert fish migration and recruitment losses. This paper investigates the operational adaptive capacity of water systems to mitigate climate change impacts on both hydropower and aquatic ecosystems, with a detailed representation of fish species recruitment response to flow regime changes. The methodology framework combines hydroclimatic modeling, explicit stochastic reservoir operation modeling, and predictive modeling of migratory fish recruitment abundance, illustrated using the large-scale hydropower system of the Paraná River Basin in Brazil. Results identified that operating policies can be adapted to improve hydropower production under a changing climate with drier conditions by 2% to 8% compared with current operating policies. Although insufficient to eliminate all energy losses that climate change may cause, the optimized operation provided flexibility to adjust flow releases and reduce the likelihood of future severe multiyear deficits, which are very harmful to fish populations. Adapting operation to climate change sacrificed fish recruitment performance over a few years of the time horizon to maintain an overall higher storage, but it also improved the chances of producing flow releases in magnitude, timing, and duration during long drier periods that prevented more severe impacts of climate change on fish recruitment and population. This indicates that it might be possible to have synergies in adapting reservoir operation to not only prevent energy losses, but also to improve fish recruitment under climate change. The ecosystem resiliency under adapted operation increased up to 2 times compared with the isolated climate change effect. [ABSTRACT FROM AUTHOR]

Knowledge and application of the Sustainable Development Goals (SDG) in the Private Natural Heritage Reserve management can help guide the sustainable use of the reserve's resources, whatever their identity and economic vocation. In addition, they ensure development with a focus on social, economic, and environmental concerns, as proposed in the 2030 Agenda. This study aims to investigate the relationship between the SDGs and the Brazilian PNHR management proposals, identifying the relevance and role of the PNHR in meeting the proposed goals by the year 2030. The study surveyed 142 PNHRs using a structured questionnaire in which their representatives assessed the level of relevance of the 17 SDGs regarding environmental conditions and local reality. The analysis compared the data concerning biomes and geographic region; cluster analysis was performed to observe similar responses, and principal component analysis to verify the relative importance between the scores assigned to the SDGs. The study created graphs based on the motivations for creating and using the PNHR. The PNHR showed alignment with the fulfillment of SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), SDG 15 (Life on Earth), and SDG 3 (Good Health and Well-being). All respondents recognize discussions about the environment and sustainable development allied to nature conservation as a priority for achieving the SDGs. It is possible to recognize the importance of strengthening a space for coexistence between the local population and the PNHR to implement regular and transformative actions in favor of conservation and sustainable development. [ABSTRACT FROM AUTHOR]

The inclusion of Sustainable Development Goals (SDGs) in climate mitigation pathways is critical and can be reached by assessing their consequences through the deployment of appropriate indicators to that end. Integrated Assessment Models (IAMs) are important tools for understanding possible impacts caused by adopting new policies. We investigate terrestrial biodiversity trends (life on land: SDG 15) for three different climate mitigation scenarios for Brazil: (1) A scenario compatible with a world that maintains its current policies with current deforestation rates in the Amazon and the Cerrado biomes; (2) A scenario in which Brazil fulfils its Nationally Determined Contribution (NDC); and (3) A scenario compatible with a world that limits warming to 1.5°C. We use the Brazilian Land-Use and Energy System model (BLUES), a national IAM, to show the implications of the transitions involved in the above-mentioned scenarios for the country up to 2050. We conduct a post-processing analysis using consolidated biodiversity indicators to emphasize how different IAM greenhouse gas (GHG) emissions mitigation solutions present distinct positive and negative potential impacts on biodiversity in Brazil. However, our analysis does not consider the impacts associated with climate change, but only the risks imposed by mitigation policies. Our results indicate that biodiversity loss decreases in the scenarios from (1) to (3), implying that stronger climate change mitigation actions could result in smaller biodiversity losses. We conclude that Brazil has the opportunity to align its biodiversity and climate goals through nature-based solutions (NBS), such as forest conservation, restoration, pasture recovery, and the use of crop-pasture and agroforestry systems. [ABSTRACT FROM AUTHOR]

Deforestation of tropical forests has been a critical issue affecting climate change mitigation and biodiversity conservation. Reforestation strives to remedy this situation, yet it is futile as long as deforestation of primary forests continues. Since deforestation is partly motivated by the demand for valuable tropical wood, reforestation should focus not only on planting native tree species, but specifically on a high diversity of native tree species with high-quality wood. However, the eco-physiological information required for growing such species is limited, and their resilience to drought events is unknown. Here, we focused on four native tropical wood tree species identified as suitable for Brazil's Atlantic Forest reforestation. Growth, carbon assimilation, water-use and xylem hydraulics were studied in seedlings of the two legume species Dalbergia nigra and Plathymenia foliolosa and the two non-legume species Cariniana legalis and Zeyheria tuberculosa. Seedlings were monitored weekly for 9 consecutive weeks, three to five weeks of which under induced drought. Growth and carbon assimilation were 25–65 per cent higher in the legume vs. non-legume species. In turn, non-legume species mostly avoided the drought by stomatal closure, producing a 50 per cent higher water-use efficiency (WUE) compared with the legume species. The average water potential at 50 per cent stomatal conductivity (Ψgs50) for legume species was −2.6 MPa, whereas for non-legume species it was −0.85 MPa. Still, each species showed a unique set of responses, indicating different growth strategies under mesic and xeric conditions. Our results indicate a divergence among legume and non-legume species, driven by a trade-off between plant productivity (carbon assimilation and growth) and plant safety (stomatal regulation and WUE). All in all, the four species of juvenile potted plants demonstrated a high capacity for recovery from drought, which supports their potential role in future reforestation under climate change. [ABSTRACT FROM AUTHOR]

The 2015 Paris Agreement relies on Nationally Determined Contributions (NDCs) to outline each country's policies and plans for reducing greenhouse gas (GHG) emissions. To strengthen global climate action and achieve the Agreement's temperature goal, it is crucial to enhance the ambition level of NDCs every 5 years. While previous studies have explored the ambition of initial NDCs, limited research has delved into the factors driving the enhancement or lack thereof in NDCs' emission reduction plans. This study employs a mixed-method design to investigate the determinants of NDC enhancement. First, we analyse the updated or revised NDCs of 111 countries using quantitative methods. Second, we conduct qualitative case studies focusing on Brazil and South Africa. Our findings reveal that countries that engaged in stakeholder consultations with civil society, business, and labour groups prior to developing their updated or revised NDCs were more likely to enhance their greenhouse gas reduction targets. These results are further supported by the case studies. South Africa conducted comprehensive consultations and submitted an enhanced GHG target, while Brazil, which did not arrange open consultations, did not improve its target. This study underscores the significance of comprehensive and transparent stakeholder engagement processes, highlighting their potential to drive enhanced NDCs. By involving diverse stakeholders, including civil society, business, and labour groups, countries can foster greater ambition and effectiveness in their climate action, ultimately contributing to the global effort to combat climate change. [ABSTRACT FROM AUTHOR]

Characterization of regrowing forests is vital for understanding forest dynamics to assess the impacts on carbon stocks and to support sustainable forest management. Although remote sensing is a key tool for understanding and monitoring forest dynamics, the use of exclusively remotely sensed data to explore the effects of different variables on regrowing forests across all biomes in Brazil has rarely been investigated. Here, we analyzed how environmental and human factors affect regrowing forests. Based on Brazil's secondary forest age map, 3060 locations disturbed between 1984 and 2018 were sampled, interpreted and analyzed in different biomes. We interpreted the time since disturbance for the sampled pixels in Google Earth Engine. Elevation, slope, climatic water deficit (CWD), the total Nitrogen of soil, cation exchange capacity (CEC) of soil, surrounding tree cover, distance to roads, distance to settlements and fire frequency were analyzed in their importance for predicting aboveground biomass (AGB) and tree cover derived from global forest aboveground biomass map and tree cover map, respectively. Results show that time since disturbance interpreted from satellite time series is the most important predictor for characterizing AGB and tree cover of regrowing forests. AGB increased with increasing time since disturbance, surrounding tree cover, soil total N, slope, distance to roads, distance to settlements and decreased with larger fire frequency, CWD and CEC of soil. Tree cover increased with larger time since disturbance, soil total N, surrounding tree cover, distance to roads, distance to settlements, slope and decreased with increasing elevation and CWD. These results emphasize the importance of remotely sensing products as key opportunities to improve the characterization of forest regrowth and to reduce data gaps and uncertainties related to forest carbon sink estimation. Our results provide a better understanding of regional forest dynamics, toward developing and assessing effective forest‐related restoration and climatic mitigation strategies. [ABSTRACT FROM AUTHOR]

• The questionnaire assessed environmental awareness and knowledge about CCS technology. • The interviews were conducted using a face-to-face approach. • A structured research was employed using an ordinal qualitative scale. • Respondents were aware of the climate change. • Climate change mitigation actions are not a priority for respondents. Carbon Capture and Storage (CCS) is considered an important option to mitigate climate change. However, the success of the new technology does not only depend on engineering practices and techniques but also involves social, political, and economic factors, as well as public acceptance. The discussion about CCS in Brazil is recent and few papers addressing Brazilian public perception and engagement with CCS were found. In this sense, this paper aims to analyze the environmental awareness about climate change and the citizens' perception of CCS technology. A public perception survey was conducted with 800 people in two Brazilian cities. Descriptive statistical techniques combined with hypothesis tests were performed to depict the results and to verify associations between different demographic groups to climate change issues and support for the development of CCS technology in Brazil. The results show that the public is aware of climate change and its consequences. However, despite public support for governmental development and investments in CCS technology, investments to mitigate climate change are not a priority for the population. Only 2% and 5% of interviewed citizens in the cities of São Mateus and Vitória, respectively, considered investments in climate change mitigation as a priority. More than 70% of respondents considered that other social elements, as health, public safety, and job creation, should be prioritized by the Brazilian government. The results suggest that the population needs more information about CCS technology and its impacts. [Display omitted] [ABSTRACT FROM AUTHOR]

Fragmented tropical forest landscapes preserve much of the remaining biodiversity and carbon stocks. Climate change is expected to intensify droughts and increase fire hazard and fire intensities, thereby causing habitat deterioration, and losses of biodiversity and carbon stock losses. Understanding the trajectories that these landscapes may follow under increased climate pressure is imperative for establishing strategies for conservation of biodiversity and ecosystem services. Here, we used a quantitative predictive modelling approach to project the spatial distribution of the aboveground biomass density (AGB) by the end of the 21st century across the Brazilian Atlantic Forest (AF) domain. To develop the models, we used the maximum entropy method with projected climate data to 2100, based on the Intergovernmental Panel on Climate Change Representative Concentration Pathway (RCP) 4.5 from the fifth Assessment Report. Our AGB models had a satisfactory performance (area under the curve > 0.75 and p value <.05). The models projected a significant increase of 8.5% in the total carbon stock. Overall, the projections indicated that 76.9% of the AF domain would have suitable climatic conditions for increasing biomass by 2100 considering the RCP 4.5 scenario, in the absence of deforestation. Of the existing forest fragments, 34.7% are projected to increase their AGB, while 2.6% are projected to have their AGB reduced by 2100. The regions likely to lose most AGB—up to 40% compared to the baseline—are found between latitudes 13° and 20° south. Overall, although climate change effects on AGB vary latitudinally for the 2071–2100 period under the RCP 4.5 scenario, our model indicates that AGB stocks can potentially increase across a large fraction of the AF. The patterns found here are recommended to be taken into consideration during the planning of restoration efforts, as part of climate change mitigation strategies in the AF and elsewhere in Brazil. [ABSTRACT FROM AUTHOR]

The Intergovernmental Panel on Climate Change and the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services have emphasised unequivocal evidences about the impact of human actions on climate and biodiversity at alarming rates. In Brazilian terms, 2019 has been marked by controversial discussions among politicians and environmentalists, leading to misinformation and misinterpretations that clearly motivate the continuous collection and scientific analysis of data to support sustainable solutions. Aiming at dealing with this issue, this manuscript brings two contributions: (i) the creation of the Brazilian Forest Dataset, including Brazilian seed plants, Fraction of Absorbed Photosynthetically Active Radiation, meteorological and geographical data composing 8,482 attributes to model and predict 20 vegetation types; and (ii) the feasibility analysis on modelling this dataset in light of supervised machine learning algorithms, so we devise confident results on the Brazilian biodiversity. Experimental results confirm Random Forest and Support Vector Machines successfully adjust models, enabling researchers to predict the occurrence of specific types of vegetation in different regions of Brazil as well as analyse how the prediction accuracy changes along time after the collection of new data. Our contributions bring important tools to support the study on the evolution of the Brazilian biodiversity. [ABSTRACT FROM AUTHOR]

Land‐use change (LUC)‐related greenhouse gas (GHG) emissions determine largely whether bioenergy is a suitable option for climate change mitigation. This study assesses how LUC emissions influence demand for bioenergy to mitigate GHG emissions, and how this affects the energy mix, using Brazil as a case study. A methodological framework is applied linking bioenergy supply curves, with associated costs and spatially explicit LUC emissions, to a bottom‐up energy system model. Furthermore, the influence of four key determining parameters is assessed: agricultural productivity, time horizon, natural succession (NS), and the use of dynamic emission factors (EFs). Demand for new bioenergy plantations range from 0.5 to 6.7 EJ in 2050, and is avoided when its EF reaches above 15 kg CO2/GJbiomass. Dynamic EFs result in earlier and larger use of bioenergy. Static EFs attenuate all emissions evenly over time, resulting in relative high emissions around 2050 when the carbon budget is most stringent. This in contrast to dynamic EFs, having early high peaks because of clearance of natural vegetation, but relatively small long‐term emissions when the carbon budget is most stringent. Exclusion of NS, in combination with spared agricultural land, results in a demand of 6.7 EJ, because of its low carbon penalty. Assuming that land is spared due to continuous yield increase (which is the reason to include NS as and EF component), bypasses the fact that yield improvements (that make those lands available) take place because of demand for bioenergy. When low‐carbon biomass is in limited availability, increasing electrification is observed, leading to electric capacity increase of 62% (mainly wind and solar energy), and a 12% energy system costs increase. Inclusion of spatiotemporal explicit supply potential and LUC emissions leads to improved bioenergy deployment pathways that come closer to the real situation as the dynamic nature of LUC emissions is included. [ABSTRACT FROM AUTHOR]

The usefulness of global integrated assessment model (IAM) results for policy recommendation in specific regions has not been fully assessed to date. This study presents the variation in results across models for a given region, and what might be behind this variation and how model assumptions and structures drive results. Understanding what drives the differences across model results is important for national policy relevance of global scenarios. We focus on the use of bioenergy in Brazil, a country expected to play an important role in future bioenergy production. We use results of the Stanford University Energy Modeling Forum's 33rd Study (EMF-33) model comparison exercise to compare and assess projections of Brazil's bioenergy pathways under climate mitigation scenarios to explore how 10 global IAMs compare to recent trends in the country. We find that, in their current form, global IAMs have limited potential to supply robust insights into regional mitigation strategies. Our results suggest fertile ground for a new research agenda to improve regional representation in global IAMs with improved spatial and technological resolutions. [ABSTRACT FROM AUTHOR]